![](/images/graphics-bg.png)
Predicting Adolescent Idiopathic Scoliosis among Chinese Children and Adolescents
Joint Authors
Yan, Bin
Lu, Xinhai
Qiu, Qihua
Nie, Guohui
Huang, Yeen
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-20
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Objective.
Adolescent idiopathic scoliosis (AIS) affects 1%-4% of adolescents in the early stages of puberty, but there is still no effective prediction method.
This study aimed to establish a prediction model and validated the accuracy and efficacy of this model in predicting the occurrence of AIS.
Methods.
Data was collected from a population-based school scoliosis screening program for AIS in China.
A sample of 884 children and adolescents with the radiological lateral Cobb angle≥10° was classified as an AIS case, and 895 non-AIS subjects with a Cobb angle<10° were randomly selected from the screening system.
All selected subjects were screened by visual inspection of clinical signs, the Adam’s forward-bending test (FBT), and the measurement of angle of trunk rotation (ATR).
LR and receiver operating characteristic (ROC) curves were used to preliminarily screen the influential factors, and LR models with different adjusted weights were established to predict the occurrence of AIS.
Results.
Multivariate LR and ROC curves indicated that angle of thoracic rotation (adjusted odds ratios AOR=5.18−10.06), angle of thoracolumbar rotation (AOR=4.67−7.22), angle of lumbar rotation (AOR=6.97−8.09), scapular tilt (area under the curve AUC=0.77, 95% CI: 0.75-0.80), shoulder-height difference, lumbar concave, and pelvic tilt were the risk predictors for AIS.
LR models with different adjusted weights (by AOR, AUC, and AOR+AUC) performed similarly in predicting the occurrence of AIS compared with multivariate LR.
The sensitivity (82.55%-83.27%), specificity (82.59%-83.33%), Youden’s index (0.65-0.67), positive predictive value (82.85%-83.58%), negative predictive value (82.29%-83.03%), and total accuracy (82.57%-83.30%) manifested that LR could accurately identify patients with AIS.
Conclusions.
LR model is a relatively high accurate and feasible method for predicting AIS.
Increased performance of LR models using clinically relevant variables offers the potential to early identify high-risk groups of AIS.
American Psychological Association (APA)
Yan, Bin& Lu, Xinhai& Qiu, Qihua& Nie, Guohui& Huang, Yeen. 2020. Predicting Adolescent Idiopathic Scoliosis among Chinese Children and Adolescents. BioMed Research International،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1131943
Modern Language Association (MLA)
Yan, Bin…[et al.]. Predicting Adolescent Idiopathic Scoliosis among Chinese Children and Adolescents. BioMed Research International No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1131943
American Medical Association (AMA)
Yan, Bin& Lu, Xinhai& Qiu, Qihua& Nie, Guohui& Huang, Yeen. Predicting Adolescent Idiopathic Scoliosis among Chinese Children and Adolescents. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1131943
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131943